Integrate and Deploy Machine Learning at the Edge with Embedded Software Containers

Learn how to effectively integrate and deploy machine learning solutions at the edge using embedded software containers in this technical talk from Semir Haddad, Chief Product and Strategy Officer at MicroEJ. Explore the challenges developers face when incorporating neural networks into complete applications, including resource sharing, event synchronization, and codebase integration. Discover how embedded software container solutions can address deployment complexities and resource provisioning without disrupting device operations. While cloud-native solutions like Docker and Kubernetes aren't feasible for TinyML applications, understand how their underlying concepts can be adapted using platforms like MicroEJ to streamline AI integration and deployment at the tiny edge. Gain practical insights into managing neural networks as components of larger systems and implementing efficient deployment strategies for edge computing environments.